Collaboration servers handle wide varieties and large amounts of data for participants of a collaboration service and typically store data in a single storage substrate like a Sequential Query Language (SQL) server. This behavior may result in resource bottlenecks, poor scalability, and high cost for data storage. In situations where the deployments include large amounts of data such as tens of terabytes of files, the challenge of managing data storage for collaboration services becomes even more significant.
Furthermore, different types of data such as structured data or unstructured data (“blob”) may be processed and accessed differently by the storage and processing systems with varying overhead requirements. If one type of data does not require the same overhead for processing or is not accessed in the same way as another type, subjecting both types to the same treatment may result in wasted resources and increased cost of managing the storage of the data.